Embodiments of the invention relate to determining a drop point in a list of results and adjusting the list of results based on the drop point. In particular, results may be removed from the list or added to the list based on the drop point.
Companies often host web sites on the World Wide Web (“WWW” or “web”) to sell products. If a customer is interested in a first product, companies would like to recommend additional products for purchase by the customer.
Many web sites today employ three types of search:
1) Paid Search—in which keywords are purchased by a company hosting a web site, and customers who are performing searches are directed to the web site by external search engines.
2) Natural Search—in which customers find search engine links related to their search terms and click the links to be routed to the site.
3) Onsite Search—in which customers at a company's web site use the search facility of the web site and explore the various products returned for a search.
To generate relevant product recommendations that the customer might be interested in viewing and/or purchasing, a monitoring system collects historical data regarding what products were most viewed and/or purchased by other customers at this web site who used the same or similar search terms within the realm of any of the above three types of searches.
Some conventional systems consolidate certain search terms and control weighting of various types of search activities and product activities. Some conventional systems require analysis of the search term recommendations for their relevancy and manual selection of product recommendations to fill in where either:
1) the recommendations generated fall short of a desired number of recommendations; and/or
2) sub-standard recommendations need to be overridden with better manual selections.
Thus, there is a need for an improved technique for generating recommendations based on search terms.